|Radiomics: the bridge between medical imaging and personalized medicine|
P Lambin, RTH Leijenaar, TM Deist, J Peerlings, EEC De Jong, ...
Nature reviews Clinical oncology 14 (12), 749-762, 2017
|Clinical evaluation of atlas and deep learning based automatic contouring for lung cancer|
T Lustberg, J van Soest, M Gooding, D Peressutti, P Aljabar, ...
Radiotherapy and Oncology 126 (2), 312-317, 2018
|Distributed learning: developing a predictive model based on data from multiple hospitals without data leaving the hospital–a real life proof of concept|
A Jochems, TM Deist, J Van Soest, M Eble, P Bulens, P Coucke, W Dries, ...
Radiotherapy and Oncology 121 (3), 459-467, 2016
|Machine learning algorithms for outcome prediction in (chemo) radiotherapy: An empirical comparison of classifiers|
TM Deist, FJWM Dankers, G Valdes, R Wijsman, IC Hsu, C Oberije, ...
Medical physics 45 (7), 3449-3459, 2018
|Decision support systems for personalized and participative radiation oncology|
P Lambin, J Zindler, BGL Vanneste, L Van De Voorde, D Eekers, ...
Advanced drug delivery reviews 109, 131-153, 2017
|Infrastructure and distributed learning methodology for privacy-preserving multi-centric rapid learning health care: euroCAT|
TM Deist, A Jochems, J van Soest, G Nalbantov, C Oberije, S Walsh, ...
Clinical and translational radiation oncology 4, 24-31, 2017
|Developing and validating a survival prediction model for NSCLC patients through distributed learning across 3 countries|
A Jochems, TM Deist, I El Naqa, M Kessler, C Mayo, J Reeves, S Jolly, ...
International Journal of Radiation Oncology* Biology* Physics 99 (2), 344-352, 2017
|Nomogram predicting response after chemoradiotherapy in rectal cancer using sequential PETCT imaging: a multicentric prospective study with external validation|
RGPM van Stiphout, V Valentini, J Buijsen, G Lammering, E Meldolesi, ...
Radiotherapy and Oncology 113 (2), 215-222, 2014
|Development and evaluation of an online three-level proton vs photon decision support prototype for head and neck cancer–Comparison of dose, toxicity and cost-effectiveness|
Q Cheng, E Roelofs, BLT Ramaekers, D Eekers, J van Soest, T Lustberg, ...
Radiotherapy and Oncology 118 (2), 281-285, 2016
|Fractal-based radiomic approach to predict complete pathological response after chemo-radiotherapy in rectal cancer|
D Cusumano, N Dinapoli, L Boldrini, G Chiloiro, R Gatta, C Masciocchi, ...
La radiologia medica 123 (4), 286-295, 2018
|Magnetic resonance, vendor-independent, intensity histogram analysis predicting pathologic complete response after radiochemotherapy of rectal cancer|
N Dinapoli, B Barbaro, R Gatta, G Chiloiro, C Casà, C Masciocchi, ...
International Journal of Radiation Oncology* Biology* Physics 102 (4), 765-774, 2018
|Standardized data collection to build prediction models in oncology: a prototype for rectal cancer|
E Meldolesi, J Van Soest, A Damiani, A Dekker, AR Alitto, M Campitelli, ...
Future Oncology 12 (1), 119-136, 2016
|An umbrella protocol for standardized data collection (SDC) in rectal cancer: a prospective uniform naming and procedure convention to support personalized medicine|
E Meldolesi, J van Soest, N Dinapoli, A Dekker, A Damiani, ...
Radiotherapy and Oncology 112 (1), 59-62, 2014
|The radiation oncology ontology (ROO): Publishing linked data in radiation oncology using semantic web and ontology techniques|
A Traverso, J Van Soest, L Wee, A Dekker
Medical physics 45 (10), e854-e862, 2018
|Big Data in radiation therapy: challenges and opportunities|
T Lustberg, J van Soest, A Jochems, T Deist, Y van Wijk, S Walsh, ...
The British journal of radiology 90 (1069), 20160689, 2017
|Distributed learning to protect privacy in multi-centric clinical studies|
A Damiani, M Vallati, R Gatta, N Dinapoli, A Jochems, T Deist, ...
Conference on artificial intelligence in medicine in europe, 65-75, 2015
|VATE: VAlidation of high TEchnology based on large database analysis by learning machine|
E Meldolesi, J van Soest, AR Alitto, R Autorino, N Dinapoli, A Dekker, ...
Colorectal Cancer 3 (5), 435-450, 2014
|Validation of a rectal cancer outcome prediction model with a cohort of Chinese patients|
L Shen, J van Soest, J Wang, J Yu, W Hu, YUT Gong, V Valentini, Y Xiao, ...
Oncotarget 6 (35), 38327, 2015
|Towards a modular decision support system for radiomics: A case study on rectal cancer|
R Gatta, M Vallati, N Dinapoli, C Masciocchi, J Lenkowicz, D Cusumano, ...
Artificial intelligence in medicine 96, 145-153, 2019
|Distributed learning on 20 000+ lung cancer patients–The Personal Health Train|
TM Deist, FJWM Dankers, P Ojha, MS Marshall, T Janssen, C Faivre-Finn, ...
Radiotherapy and Oncology 144, 189-200, 2020